Dataset Information

Clinical-Radiomic Analysis for Pretreatment Prediction of Objective Response to First Transarterial Chemoembolization in Hepatocellular Carcinoma.

ABSTRACT:

Background

The preoperative selection of patients with intermediate-stage hepatocellular carcinoma (HCC) who are likely to have an objective response to first transarterial chemoembolization (TACE) remains challenging.

Objective

To develop and validate a clinical-radiomic model (CR model) for preoperatively predicting treatment response to first TACE in patients with intermediate-stage HCC.

Methods

A total of 595 patients with intermediate-stage HCC were included in this retrospective study. A tumoral and peritumoral (10 mm) radiomic signature (TPR-signature) was constructed based on 3,404 radiomic features from 4 regions of interest. A predictive CR model based on TPR-signature and clinical factors was developed using multivariate logistic regression. Calibration curves and area under the receiver operating characteristic curves (AUCs) were used to evaluate the model's performance.

Results

The final CR model consisted of 5 independent predictors, including TPR-signature (p < 0.001), AFP (p = 0.004), Barcelona Clinic Liver Cancer System Stage B (BCLC B) subclassification (p = 0.01), tumor location (p = 0.039), and arterial hyperenhancement (p = 0.050). The internal and external validation results demonstrated the high-performance level of this model, with internal and external AUCs of 0.94 and 0.90, respectively. In addition, the predicted objective response via the CR model was associated with improved survival in the external validation cohort (hazard ratio: 2.43; 95% confidence interval: 1.60-3.69; p < 0.001). The predicted treatment response also allowed for significant discrimination between the Kaplan-Meier curves of each BCLC B subclassification.

Conclusions

The CR model had an excellent performance in predicting the first TACE response in patients with intermediate-stage HCC and could provide a robust predictive tool to assist with the selection of patients for TACE.

SUBMITTER: Chen M

PROVIDER: S-EPMC7923935 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Clinical-Radiomic Analysis for Pretreatment Prediction of Objective Response to First Transarterial Chemoembolization in Hepatocellular Carcinoma.

Chen Mingyu M Cao Jiasheng J Hu Jiahao J Topatana Win W Li Shijie S Juengpanich Sarun S Lin Jian J Tong Chenhao C Shen Jiliang J Zhang Bin B Wu Jennifer J Pocha Christine C Kudo Masatoshi M Amedei Amedeo A Trevisani Franco F Sung Pil Soo PS Zaydfudim Victor M VM Kanda Tatsuo T Cai Xiujun X

Liver cancer 20210107 1

<h4>Background</h4>The preoperative selection of patients with intermediate-stage hepatocellular carcinoma (HCC) who are likely to have an objective response to first transarterial chemoembolization (TACE) remains challenging.<h4>Objective</h4>To develop and validate a clinical-radiomic model (CR model) for preoperatively predicting treatment response to first TACE in patients with intermediate-stage HCC.<h4>Methods</h4>A total of 595 patients with intermediate-stage HCC were included in this re ...[more]

PMID: 33708638

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Project description:Transarterial chemoembolization (TACE) is the mainstay of treatment for patients with intermediate/advanced stage or unresectable hepatocellular carcinoma (HCC). Despite the palliative nature of TACE treatment, embolizing the tumor feeding vessels and leading to progressive tumor necrosis, complete response (CR) after TACE could still be observed in a certain population. Thus, this study aimed to investigate both the predictors for CR and the long-term prognosis of the patients with CR after TACE. The study recruited new diagnosed HCC patients initially treated with TACE from 2010 to 2013. Post TACE response was assessed by scheduled image studies according to the modified Response Evaluation Criteria in Solid Tumors (mRECIST). Then, pre-TACE factors were compared between patients with and without CR. After the first session of TACE, 22.3% of the 669 TACE treated patients achieved CR. During a median of 26.6 months follow-up, patients with CR had better overall survival than those without (median: 35.8 vs. 24.0 months, P<0.001). By multivariate logistic regression analysis, Child-Turcotte-Pugh class B (OR: 0.419, P=0.005), tumor burden beyond up-to-7 criteria (OR: 0.118, P<0.001), bilobar tumor extent (OR: 0.236, P<0.001), higher alpha-fetoprotein (AFP) level (≥20 ng/ml, OR: 0.614, P=0.039) and higher platelet counts (>150 k/μl, OR: 0.482, P=0.002) were unfavorable predictors for CR after first TACE. In addition, macrovascular invasion (HR: 3.113, P=0.001) and higher AFP levels (≥15 ng/ml, HR: 2.601, P=0.007) were predictors for early HCC recurrence whereas diabetes mellitus (DM) (HR: 2.166, P=0.006) was the only significant predictor for late HCC recurrence in CR patients. In conclusion, more than one-fifth of HCC patients achieved CR after first TACE and these patients had favorable prognosis. Furthermore, tailored post-TACE follow-up strategies shall be considered in patients with different risk factors of early or late recurrence after CR.

Project description:Transarterial chemoembolization (TACE) is a commonly used treatment modality in hepatocellular carcinoma (HCC). The ability to identify patients who will respond to TACE represents an important clinical need, and tumor gene expression patterns may be associated with TACE response. We investigated whether tumor transcriptome is associated with TACE response in patients with HCC. We analyzed transcriptome data of treatment-naïve tumor tissues from a Chinese cohort of 191 HCC patients, including 105 patients who underwent TACE following resection with curative intent. We then developed a gene signature, TACE Navigator, which was associated with improved survival in patients that received either adjuvant or post-relapse TACE. To validate our findings, we applied our signature in a blinded manner to three independent cohorts comprising an additional 130 patients with diverse ethnic backgrounds enrolled in three different hospitals who received either adjuvant TACE or palliative TACE. TACE Navigator stratified patients into Responders and Non-Responders which was associated with improved survival following TACE in our test cohort (Responders: 67 months vs Non-Responders: 39.5 months, p<0.0001). In addition, multivariable Cox model demonstrates that TACE Navigator was independently associated with survival (HR: 9.31, 95% CI: 3.46-25.0, p<0.001). In our validation cohorts, the association between TACE Navigator and survival remained robust in both Asian patients who received adjuvant TACE (Hong Kong: 60 months vs 25.6 months p=0.007; Shandong: 61.3 months vs 32.1 months, p=0.027) and European patients who received TACE as primary therapy (Mainz: 60 months vs 41.5 months, p=0.041). These results indicate that a TACE-specific molecular classifier is robust in predicting TACE response. This gene signature can be used to identify patients who will have the greatest survival benefit after TACE treatment and enable personalized treatment modalities for patients with HCC.

Project description:PurposeTo investigate the role of contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics for pretherapeutic prediction of the response to transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC).MethodsOne hundred and twenty-two HCC patients (objective response, n = 63; non-response, n = 59) who received CE-MRI examination before initial TACE were retrospectively recruited and randomly divided into a training cohort (n = 85) and a validation cohort (n = 37). All HCCs were manually segmented on arterial, venous and delayed phases of CE-MRI, and total 2367 radiomics features were extracted. Radiomics models were constructed based on each phase and their combination using logistic regression algorithm. A clinical-radiological model was built based on independent risk factors identified by univariate and multivariate logistic regression analyses. A combined model incorporating the radiomics score and selected clinical-radiological predictors was constructed, and the combined model was presented as a nomogram. Prediction models were evaluated by receiver operating characteristic curves, calibration curves, and decision curve analysis.ResultsAmong all radiomics models, the three-phase radiomics model exhibited better performance in the training cohort with an area under the curve (AUC) of 0.838 (95% confidence interval (CI), 0.753 - 0.922), which was verified in the validation cohort (AUC, 0.833; 95% CI, 0.691 - 0.975). The combined model that integrated the three-phase radiomics score and clinical-radiological risk factors (total bilirubin, tumor shape, and tumor encapsulation) showed excellent calibration and predictive capability in the training and validation cohorts with AUCs of 0.878 (95% CI, 0.806 - 0.950) and 0.833 (95% CI, 0.687 - 0.979), respectively, and showed better predictive ability (P = 0.003) compared with the clinical-radiological model (AUC, 0.744; 95% CI, 0.642 - 0.846) in the training cohort. A nomogram based on the combined model achieved good clinical utility in predicting the treatment efficacy of TACE.ConclusionCE-MRI radiomics analysis may serve as a promising and noninvasive tool to predict therapeutic response to TACE in HCC, which will facilitate the individualized follow-up and further therapeutic strategies guidance in HCC patients.

Project description:BackgroundDrug-eluting embolic transarterial chemoembolization (DEE-TACE) is an advance in TACE technique. However, at present there is insufficient evidence to support that DEE-TACE is superior to conventional TACE (cTACE) for hepatocellular carcinoma (HCC). The aim of this meta-analysis is to evaluate the efficacy and safety of TACE with CalliSpheres® microspheres (CSM-TACE) compared with cTACE in patients with HCC.Data sourcesPubMed, Embase, Web of Science, CNKI and Wanfang Databases were searched to identify relevant articles published before March 26, 2020. The data regarding treatment response, survival profile, adverse events and liver function indexes were retrieved.ResultsA total of 16 studies with 1454 HCC patients (722 treated with CSM-TACE and 732 with cTACE) were included. Patients receiving CSM-TACE had higher 1-month complete response (CR), objective response rate (ORR), disease control rate (DCR) (odds ratio (OR): 2.00, 95% confidence interval (95% CI): 1.29-3.09; OR: 2.87, 95% CI: 2.15-3.83; OR: 2.01, 95% CI: 1.37-2.95, respectively), 3-month CR, ORR, DCR (OR: 4.04, 95%CI: 2.46-6.64; OR: 3.39, 95%CI: 2.45-4.70; OR: 1.71, 95%CI: 1.14-2.55 respectively), and 6-month CR, ORR, DCR (OR: 4.02, 95%CI: 2.26-7.16; OR: 3.00, 95%CI: 2.05-4.38; OR: 2.66, 95%CI: 1.70-4.16 respectively) than those treated with cTACE. Furthermore, CSM-TACE exhibited a trend toward improved progression free survival (hazard ratio (HR): 0.86, 95%CI: 0.67-1.11) and overall survival (HR: 0.79, 95%CI: 0.59-1.07) over cTACE although these differences did not reach statistical significance. In terms of safety, the two TACE treatments showed similar post-treatment pain (OR: 0.84, 95%CI: 0.55-1.28), fever (OR: 0.99, 95%CI: 0.60-1.63), nausea/vomiting (OR: 0.84, 95% CI: 0.60-1.17), as well as 1-month follow-up alanine aminotransferase (Mean difference (MD): -3.66, 95%CI: -10.38-3.07), aspartate aminotransferase (MD: -2.30, 95%CI: -8.91-4.31) and total bilirubin (MD: -0.15, 95%CI: -2.26-1.96).ConclusionCSM-TACE displays superior treatment response, non-inferior survival profile and safety over cTACE in HCC patients.

Project description:Magnetic resonance imaging (MRI) plays a critical role in the planning and monitoring of hepatocellular carcinomas (HCC) treated with locoregional therapies, in order to assess disease progression or recurrence. Dynamic contrast-enhanced (DCE)-MRI sequences offer temporal data on tumor enhancement characteristics which has strong prognostic value. Yet, predicting follow-up DCE-MR images from which tumor enhancement and viability can be measured, before treatment of HCC actually begins, remains an unsolved problem given the complexity of spatial and temporal information. We propose an approach to predict future DCE-MRI examinations following transarterial chemoembolization (TACE) by learning the spatio-temporal features related to HCC response from pre-TACE images. A novel Spatial-Temporal Discriminant Graph Neural Network (STDGNN) based on graph convolutional networks is presented. First, embeddings of viable, equivocal and non-viable HCCs are separated within a joint low-dimensional latent space, which is created using a discriminant neural network representing tumor-specific features. Spatial tumoral features from independent MRI volumes are then extracted with a structural branch, while dynamic features are extracted from the multi-phase sequence with a separate temporal branch. The model extracts spatio-temporal features by a joint minimization of the network branches. At testing, a pre-TACE diagnostic DCE-MRI is embedded on the discriminant spatio-temporal latent space, which is then translated to the follow-up domain space, thus allowing to predict the post-TACE DCE-MRI describing HCC treatment response. A dataset of 366 HCC's from liver cancer patients was used to train and test the model using DCE-MRI examinations with associated pathological outcomes, with the spatio-temporal framework yielding 93.5% classification accuracy in response identification, and generating follow-up images yielding insignificant differences in perfusion parameters compared to ground-truth post-TACE examinations.

Dataset Information

Clinical-Radiomic Analysis for Pretreatment Prediction of Objective Response to First Transarterial Chemoembolization in Hepatocellular Carcinoma.

Background

Objective

Methods

Results

Conclusions

Publications

Clinical-Radiomic Analysis for Pretreatment Prediction of Objective Response to First Transarterial Chemoembolization in Hepatocellular Carcinoma.

Similar Datasets

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